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CV

You can download or view my latest CV here.

Expertise in Python, SQL and Infrastructure as Code as well as Airflow, Bash, Testing, dbt, Databases, Docker, APIs and Spark. I like to design solutions (from networking and permissions through to app development) and then implement with best practices. I am keen to learn new tools and develop on the ones I already have.

Certifications

Check out my current valid certifications.

AWS Cloud Practitioner Badge AWS SysOps Administrator Associate Badge AWS Developer Associate Badge AWS Data Engineer Associate Badge AWS Solutions Architect Associate Badge HashiCorp Certified Terraform Associate Badge

Work Experience

Technical Experience

Trinity College London

Data Engineer (Hybrid) / August 2025 – present
Contract Role (9 Months)

Hard Rock Digital

Data Engineer (Remote) / January 2025 – August 2025
Permanent Role

  • Optimising and Refactoring Suboptimal Processes
    • Refactored and optimised various Airflow DAGs to adhere to best practices, improving the efficiency of DAG parsing and debugging.
    • Started the creation of documentation in DBT Cloud, utilising unit and data tests for audit purposes, as well as Snowflake.
    • Designed and built out in Terraform the new gambling self-exclusion pipeline, creating a new data model for efficiency.
    • Created several CI/CD pipelines for deployment of this pipeline, as well as testing including tools such as mypy.
    • Bootstrapped the Astronomer (Airflow) environments for our regulatory team, creating utility operators for logging and notifications.
    • Created a template for unit testing including mocking, as well as introducing data validation tools to the team.

MarketCast

Senior Cloud Engineer (Hybrid) / November 2023 – January 2025
Permanent Role

  • Designing and Implementing the Survey Database Solution
    • As part of the data architecture team, I scoped, designed and implemented our new data warehouse solution for survey data. The current file-based architecture was limiting use cases and our ability to do further look-backs for historical normative calculations.
    • Utilised AWS CDK/CloudFormation for the deployment (including several event-based Lambdas and ECS for processing the surveys). Used Redshift for the warehouse solution and dbt for modelling ELT layers within the database, orchestrated through AWS MWAA.
    • Developed a table design to preserve the metadata in the survey SPSS/SAV files and for ease of metadata filtering.
    • Built a generalised API with API Gateway, Route53 and FastAPI for database access and aggregation calculations for dashboards.
    • Implemented proper logging and alerting via SNS, CloudWatch and SQS for error catching / retries between services.
    • Integrating the database with data science ML APIs to enrich the survey data.
    • Created a standard for networking across the data architecture team, which was approved by our AWS account solution architects.
    • Collaborated with teams in the US and India to incorporate this new survey database into the backend of our new product offerings. The database is currently powering new product dashboards and various products we have migrated.
    • Utilising Redshift as our data warehouse has allowed us to calculate normative values going back years, not just months, in seconds. It has allowed us to consolidate duplicate products which all had similar architectures, reducing AWS costs by thousands per month.
    • Involved AWS in discussions as part of MAP program to help ensure best practice and design patterns for this architecture.

Data Engineer / Scientist (Hybrid) / April 2021 – November 2023

  • Automating and Optimising our Attribution Engine

    • Singularly designed and implemented full end-to-end system for Excel report generation from client requests in JIRA.
    • Utilised GPUs for nearest-neighbour ML algorithm, CTAS for Athena query optimisations and VPC optimisations (NAT and endpoints).
    • Optimised various SQL queries to reduce data scan and execution time and migrated Redshift queries to Athena.
    • Used memory profiling (memray) to track memory usage of jobs to gather training data for an ML model to predict memory usage.
    • The above had significantly improved the reliability of client deliverables, reduced their delivery time and freed up resources.
    • Moreover, we were able to reduce the cost of running a report down to a few hundred pounds from multiple thousand pounds.

  • Cost Savings, Technical Support and Implementation of Best Practices

    • Working with the SVP of Technical Architecture to help reduce our organisations AWS account costs.
    • Point of contact for AWS IAM permission issues, BitBucket access and Okta through having admin access.
    • Defined best practices for code development, unit testing, IaC and CI/CD deployments across the data science team.
    • Implemented the principle of least privilege to roles in our production accounts.
    • Conducted knowledge sharing sessions for upskilling the team, based on specific gaps in knowledge.
    • Refactored a suboptimal ETL pipeline for our TV viewing data, reducing EC2 costs by 25% and execution time from hours to minutes (PySpark from Pandas).

  • Other Things Of Note

    • Designed and implemented a pipeline for A+E for detecting ageism in advertising. This involved ingesting thousands of .mp4 assets through AWS Rekognition and AWS Transcribe using an event-based and queueing schedule (i.e. SNS, SQS and Lambda). The resulting output was queried within Athena for analysis. See the blog post here.

Non-Technical Experience

LCC Learning

Mathematics Writer (Temporary) / October 2020

Pimlico Academy

Mathematics Intervention Tutor / January 2020 – July 2020

Imperial College London

Graduate Teaching Assistant (Mathematics) / September 2019 – January 2020

University of Bath

Mathematics Senior Peer Tutor / August 2018 – May 2019
Mathematics First Year Tutor / September 2017 – May 2019
Mathematics Peer Tutor / September 2016 – May 2019

Education

University

Masters in Mathematics, MMath.
University of Bath attended from September 2015 to July 2019.
Awarded first class honours (88%).

I specialised in functional analysis and my thesis is here.

Pre-University

A-Levels in Mathematics, Further Mathematics and Chemistry.
Gravesend Grammar School attended from September 2013 to July 2015.
Awarded A*A*A*.

GCSEs.
Thamesview School attended from September 2008 to July 2013.
Awarded 8 GCSEs grade A*-C and 3 BTECs of grade Distinction.